CVE-2021-37651
CVE-2021-37651 is a high-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 7.1. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-787.
Key facts
- Severity: High (CVSS 3.x base score 7.1)
- CVSS v2: 4.6
- EPSS exploit prediction: 0% (7th percentile)
- Actively exploited: Not listed in CISA KEV
- Weakness: CWE-787
- Affected product: Google Tensorflow
- Published:
- Last modified:
Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Frequently asked questions
- What is CVE-2021-37651?
- TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
- How severe is CVE-2021-37651?
- CVE-2021-37651 has a CVSS 3.x base score of 7.1, rated high severity. It is exploitable over local access with low attack complexity, requires low privileges and no user interaction. Impact on confidentiality is high, integrity high, and availability none.
- Is CVE-2021-37651 being actively exploited?
- It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (7th percentile), an estimate of the probability of exploitation in the next 30 days.
- What products are affected by CVE-2021-37651?
- CVE-2021-37651 primarily affects Google Tensorflow. In total, 5 product configurations (CPEs) are listed as vulnerable; see the affected-products list for the exact versions.
- How do I fix CVE-2021-37651?
- Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its high severity, prioritise patching exposed systems.
- When was CVE-2021-37651 published?
- CVE-2021-37651 was published on 2021-08-12 and last updated on 2026-06-17.
References
- https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr
Affected products (5)
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
- cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*
- cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*
- cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*
- cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*
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